Top 5 Interesting Machine Learning Stats in 2022

Top 5 Interesting Machine Learning Stats in 2022

This article will summarize interesting facts about machine learning that will help you understand why it is becoming popular.
Halime Yilmaz
3 minutes

Top 5 Interesting Machine Learning Stats in 2022

Machine learning, or ML for short, is a branch of computer science that lets computers find patterns and make predictions based on how people use data to make changes without any extra or specialized programming.

The commercial and academic sectors are seeing the most remarkable growth in machine learning use. A variety of cutting-edge products are being created and introduced by these sectors.

The result is widespread interest in machine learning among relevant parties.

Some enterprise software and business intelligence tools now come with machine learning algorithms that can predict patterns and trends in the future. Using this method, data analysts can find new insights and minor differences and trends in large datasets, giving them a more comprehensive range of work.

This article will summarize essential and interesting facts about machine learning that will help you understand why it is becoming popular so quickly.

It's time to dive into the top five interesting statistics in machine learning in 2022.

Machine Learning Stats in 2022

The Market for Machine Learning

The size of the machine learning market has been going up steadily. Deep learning software is an essential part of this market, and by 2025, it is expected to be worth almost $1 billion. Also, current market research on machine learning shows that the demand for AI-powered hardware and assistants is expected to overgrow.

In order to have a better idea of what's happening in the market for machine learning, take a look at the data provided below.

  • The US market for deep learning software is expected to be worth $80 million by 2025.
  • The global market for artificial intelligence is expected to grow to $75.54 billion by 2023, with a CAGR of over 33% between 2019 and 2023.
  • The global market for deep learning is projected to reach $44.3 billion by 2027, with a CAGR of 39.2% during the forecast period.
  • At a CAGR of 37.60% from 2019 to 2026, the artificial intelligence (AI) hardware market is predicted to be worth $87.68 billion.
  • $13 trillion: The amount that AI could add to the world economy by 2030.

Interesting Stats about the Use of Machine Learning

Recent machine learning research highlights incredible levels of ML usage by businesses. With businesses racing to use technology to gain an edge, adoption rates have increased dramatically.

When it comes to industries that have embraced the use of AI software, the financial sector is at the forefront.

These apps use machine learning to sift through data and extract valuable insights. Machine learning capabilities drive the expansion, such as risk management, performance analysis, reporting, and automation.

Here are some statistics about the spread of ML:

  • AI and machine learning advances could add 14% to the world's GDP between now and 2030.
  • 16% of IT heads want to use ML in sales and marketing
  • 50% of respondents said that their companies had used AI in at least one business function.
  • Cost reductions are not discussed as much as cost increases when AI is used. For instance, 80% of people said that AI had helped them make more money.
  • Scaling up (43%), versioning ML models (41%), and getting senior buy-in are some of the biggest challenges to using machine learning.

You can also read our article if you are wondering if AI can take your job.

The Role of Machine Learning in Businesses

Corporations all across the globe have adopted ML, with the vast majority labeling themselves "early adopters." Technology has been a driving force in developing new products and services for businesses, enabling the development of intelligent processes that include AI with learning capacity. Business intelligence tools are one example. Business intelligence data from the present day will provide a clear picture of this shift.

However, there are obstacles to deploying ML, such as a shortage of data and a scarcity of talent to solve machine learning issues.

Explore the data below to discover more about the status of machine learning in the corporate world today: 

  • The predicted boost in efficiency due to AI adoption is 54 percent.
  • Nearly half, or 49%, of businesses, are investigating or making plans to adopt machine learning.
  • There are now 51% early adopters of ML in the business world.
  • Customers have reported that businesses provide them with access to virtual agents.
  • The expected ROI from using AI is 40%.
  • Only 15% of businesses utilize ML at a high level.
  • C-suite executives are currently in charge of 75% of all AI initiatives.
  • Ninety-one percent of market leaders are now investing in AI.
  • LinkedIn lists more than 44,000 positions in the United States needing machine learning and over 98,000 opportunities internationally.
  • Sixty-two percent of consumers are open to sharing their information with AI if it means an enhanced shopping or service experience.

To learn more, you can also read: Machine Learning in Business Life (2022 Use Case)

Interesting Stats about Machine Learning Use Cases

Several corporate settings have identified uses for machine learning. The technique essentially enables AI to teach a computer to learn.

Allowing computers to learn without being explicitly programmed is the foundation of machine learning.

The data below shows that ML is finding more and more uses as time goes on:

  • The number of NLP applications in customer service is projected to increase.
  • Only 14.6% of organizations claimed that they had used AI capabilities in production on a large scale.
  • Leaders in AI reported superior business results. For instance, 47% reported being able to optimize sales and marketing, while 32% reported being able to minimize operational expenses.
  • Less than 10,000 - The number of individuals with the necessary abilities to solve significant AI challenges.

Achievements in Machine Learning

The best part is about to begin. What can we expect from machine learning in the future?

Today, AI has expanded capabilities thanks to machine learning. For instance, business intelligence systems can be enhanced by adding machine learning characteristics to computers that can handle and analyze complicated data sets. Technology is in its infancy, so science fiction scenarios have a long way to go.

  • To get a feel for how far machine learning has come since its start, consider the following data.
  • Artificial intelligence developed by Google can identify lung cancer better than six human radiologists.
  • According to Indeed's 2020 Career Guide, positions using artificial intelligence are the second most sought after.
  • When Google Translate switched to GNMT, a translation system driven by machine learning, translation mistakes dropped by 60%.
  • Predictions of a patient's mortality using machine learning are accurate to within 95% of the time.
  • The machine learning techniques used to forecast patient deaths from COVID-19 were 92 percent accurate.
  • The percentage by which machine learning successfully forecasts market peaks and troughs is 62%.
  • By 2025, artificial intelligence robots will provide 75% of Japan's senior care services.
  • Speech recognition systems have an error rate of about 5%.
  • Deep learning methods provide for 40% of analytics' yearly value creation.
  • To put it another way, Google's Deep Learning software has an accuracy rate of 89% when spotting breast cancer.
  • Deep Speech, an artificial intelligence-powered voice cloning technique, can replicate a voice in only 3.7 seconds.

Final Words

We can all agree that the future will be shaped by machine learning and deep learning applications. Artificial intelligence (AI) and machine learning (ML) will play a significant role in the future success of enterprises. But despite its potential, only a small percentage of people profit from it. The appropriate implementation can lead to increased profits and reduced expenses for enterprises.

The stats on machine learning shows that the field is still through trials in the business sector and that a rising expert workforce is essential to the field's long-term success.

Cameralyze is the first no-code AI platform to help you make the most of artificial intelligence and computer vision systems. As you can see from the data above, applying AI can help you improve your operations and grow your business. And Cameralyze is the easiest and quickest way to apply machine learning and AI to your business. 

In addition, Cameralyze's intuitive interface means you don't need to know any technical details to use it to your advantage.

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